Demand

- [Voiceover] We're going to being this courseby talking about the demand for data science.Now, to make sense out of that,we first need to say what data science even is.One common definition, and I'll say more about this later,is that data science is the field that joins statisticsand programming in applied settings.Now, I have a couple of other possible definitions for this.These are ones that I made up.I like to think of it as the analysis of diverse data.Meaning, data that doesn't fit into common format,data no matter where it comes from,no matter how it's constitutedthat you need to answer your important questions.

Or even more succinctly,I like to call it inclusive analysis.Data science is data analysisthat includes all kinds of data.Anything that you can use to get insightand actionable steps out of your data.Now, that may not sound like much all on it's own.But take a look at this articlefrom the Harvard Business Review.It says Data Scientist: The Sexiest Job of the 21st Century.

Data science has rare qualities and it shows high demand.What are these rare qualities?Well, it's the ability to take unstructured data,and that can mean open text off of webpages,it can web blogs, it can mean photos, videos,it can mean any sorts of thing.The ability to take unstructured data and find order,meaning and value in that data.Now, what about the demand?Why are these qualities in high demand?Very simply, they provide insight into what's going onin peoples minds and their behaviors,and they provide competitive advantage.

Not surprisingly there's a growing need for data science.The McKinsey Global Institute projected the demandfor data science in the year 2018.And here's what they found.They said that there would be a shortageof data skills in 2018.More specifically, in the United States alonethey predicted a shortfall of anywhere from 140,000to 190,000 people with deep analytical talent.So these are the actual working data scientist,the technical people who are manipulating the dataand making it happen.

Perhaps even more significantly,they projected a shortfall of 1.5 million data savvymanagers who could make use of the datain a business setting.Who could actually put it into contextand make something happen with it.This is an enormous demand.And finally, let's just say a thingabout data science salaries.Now, here's a chart that combines datafrom the US News & World Report on the best paying jobsin the United States.And I've inserted into it data scientistusing data from a report by O'Reilly Media.

And what you see on this one,is that number one is physicians or doctors, then dentists.Data scientist would be third on this list,which is three places above lawyers.The medium salary here is $144,000,with a base salary of about $104,000.It's a very well paying field.And so, what are our conclusionsfrom this brief introduction on demand.First off, that there is high demand for data science.

Second, there's a need for both specialists,the technicians who do the data science,as well as for generalists,the contextually oriented managers and otherswho put those results into practice.And of course, the pay is excellent.And taking together these three factsgive a compelling portrait for data scienceand that's why we're going to look at it in greater detail.

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7/27/2016

Introduction to Data Science provides a comprehensive overview of modern data science: the practice of obtaining, exploring, modeling, and interpreting data. While most only think of the "big subject," big data, there are many more fields and concepts to explore. Here Barton Poulson explores disciplines such as programming, statistics, mathematics, machine learning, data analysis, visualization, and (yes) big data. He explains why data scientists are now in such demand, and the skills required to succeed in different jobs. He shows how to obtain data from legitimate open-source repositories via web APIs and page scraping, and introduces specific technologies (R, Python, and SQL) and techniques (support vector machines and random forests) for analysis. By the end of the course, you should better understand data science's role in making meaningful insights from the complex and large sets of data all around us.